方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| TAR / SETAR：用于机制转换时间序列的门限自回归模型× | 光滑转换自回归 (STAR) 模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990 | 1994 |
| 提出者≠ | Howell Tong | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| 类型≠ | Nonlinear time-series model with regime switching | Nonlinear time-series regime-switching model |
| 开创性文献≠ | Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 978-0-19-852300-6 | Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗ |
| 别名≠ | Threshold Autoregression, Self-Exciting Threshold Autoregression, SETAR Model, Eşik Otoregresyon | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| 相关≠ | 2 | 4 |
| 摘要≠ | TAR and SETAR are nonlinear autoregressive models introduced by Howell Tong (1990) that allow a time series to follow different linear dynamics in distinct regimes, separated by one or more threshold values. SETAR is the self-exciting variant, in which the threshold variable is a lagged value of the series itself, making it particularly suited to cycles, asymmetric adjustment, and limit-cycle behavior observed in economic and financial data. | The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations. |
| ScholarGate数据集 ↗ |
|
|